An example of Learning based on competences: Use of Maxima in Linear Algebra for Engineers

This paper analyzes the role of Computer Algebra Systems (CAS) in a model of learning based on competences. The proposal is an e-learning model Linear Algebra course for Engineering, which includes the use of a CAS (Maxima) and focuses on problem solving. A reference model has been taken from the Spanish Open University. The proper use of CAS is defined as an indicator of the generic ompetence: Use of Technology. Additionally, we show that using CAS could help to enhance the following generic competences: Self Learning, Planning and Organization, Communication and Writing, Mathematical and Technical Writing, Information Management and Critical Thinking.

Effect of bird age and storage system on physical properties of eggs from brown laying hens

A total of 108 eggs from a group of 100 brown laying hens housed in standard cages were analyzed. Thirty-six eggs were retired when the hens had 30 week of age, other 36 eggs were retired when the hens had 35 week of age and the remaining 36 eggs were retired five weeks afterwards. Each group of 36 eggs was radomly divided in three groups of 12 eggs. First group was analyzed at once, second group one was kept during one week in the refrigerator (5°C) and third group was kept also one week but on ambient temperature (25°C). Shell color, shell thickness, specific gravity, albumen height and Haugh units wre obtained. The bird age had significant effect on shell color and shell thickness, but the storage system had not influence on such variables. The hen age had not effect on specific gravity, but the storage system affected to this variable. Hen age and storage system had significant influence (P<0.05) on albumen height and Haugh units, and the interaction age × storage system was significant for these variables. The specific gravity had positive relations with shell thickness, yolk color, albumen height and Haugh units. It is concluded that bird age and storage system under high temperatures reduced the egg quality.

Accelerated life test of high luminosity AlGaInP LEDs

Specific tests to assess reliability of high luminosity AlInGaP LED for outdoor applications are needed. In this paper tests to propose a model involving three parameters: temperature, humidity and current have been carried out. Temperature, humidity and current accelerated model has been proposed to evaluate the reliability of this type of LED. Degradation and catastrophic failure mechanisms have been analyzed. Finally we analyze the effect of serial resistance in power luminosity degradation.

Quantity of CO2 Emissions in the Life Cycle of a Highway Infrastructure

There is strong evidence to indicate that carbon dioxide and other greenhouse gases are accumulating at unprecedented concentrations in out atmosphere contributing to global climate change. Evidence is equally strong that human activities, mainly the burning of fossil fuels, are driving force in this process (IPCC 2007). While different industries contribute varying amounts to total anthropogenic greenhouse gases, it is incumbent upon each to understand its contribution and search for sensible ways to reduce overall greenhouse gas production. The aim of this paper is the development of a methodology to determine the amount of CO2 emissions of a highway, allowing providing solutions that can improve the energy footprint and reduce its emissions

Prediction of wake effects on wind farm power production using a RANS approach. Part II. Offshore: Case studies from the UPWIND project

The estimation of power losses due to wind turbine wakes is crucial to understanding overall wind farm economics. This is especially true for large offshore wind farms, as it represents the primary source of losses in available power, given the regular arrangement of rotors, their generally largerdiameter and the lower ambient turbulence level, all of which conspire to dramatically affect wake expansion and, consequently, the power deficit. Simulation of wake effects in offshore wind farms (in reasonable computational time) is currently feasible using CFD tools. An elliptic CFD model basedon the actuator disk method and various RANS turbulence closure schemes is tested and validated using power ratios extracted from Horns Rev and Nysted wind farms, collected as part of the EU-funded UPWIND project. The primary focus of the present work is on turbulence modeling, as turbulent mixing is the main mechanism for flow recovery inside wind farms. A higher-order approach, based on the anisotropic RSM model, is tested to better take into account the imbalance in the length scales inside and outside of the wake, not well reproduced by current two-equation closure schemes.

Response threshold models and stochastic learning automata for self-coordination of heterogeneous multi-task distribution in multi-robot systems.

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-selection of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested in a decentralized solution where the robots themselves autonomously and in an individual manner, are responsible for selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-task distribution problem and we propose a solution using two different approaches by applying Response Threshold Models as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

Fusion of probabilistic knowledge-based classification rules and learning automata for automatic recognition of digital images

In this paper, the fusion of probabilistic knowledge-based classification rules and learning automata theory is proposed and as a result we present a set of probabilistic classification rules with self-learning capability. The probabilities of the classification rules change dynamically guided by a supervised reinforcement process aimed at obtaining an optimum classification accuracy. This novel classifier is applied to the automatic recognition of digital images corresponding to visual landmarks for the autonomous navigation of an unmanned aerial vehicle (UAV) developed by the authors. The classification accuracy of the proposed classifier and its comparison with well-established pattern recognition methods is finally reported.

Quantity of CO2 Emissions in the Life Cycle of a Highway Infrastructure.

The complexity of climate change and its evolution during the last few years has a positive impact on new developments and approaches to reduce the emissions of CO2. Looking for a methodology to evaluate the sustainability of a roadway, a tool has been developed. Life Cycle Assessment (LCA) is being accepted by the road industry to measure and evaluate the environmental impacts of an infrastructure, as the energy consumption and carbon footprint. This paper describes the methodology to calculate the CO2 emissions associated with the energy embodied on a roadway along its life cycle, including construction, operations and demolition. It will assist to find solutions to improve the energy footprint and reduce the amount of CO2 emissions. Details are provided of both, the methodology and the data acquisition. This paper is an application of the methodology to the Spanish highways, using a local database. Two case studies and a practical example are studied to show the model as a decision support for sustainable construction in the road industry.

Effect of Thermal Relaxation on LSP Induced Residual Stresses and Fatigue Life Enhancement of AISI 316L stainless steel

Effect of Thermal Relaxation on LSP Induced Residual Stresses and Fatigue Life Enhancement of AISI 316L stainless steel

Reduction of critical mass in a chemotaxis system by external application of a chemoattractant

In this paper we study non-negative radially symmetric solutions of a parabolic-elliptic Keller-Segel system. The system describes the chemotactic movement of cells under the additional circumstance that an external application of a chemo attractant at a distinguished point is introduced.

Finite element code-based modeling of a multi-feature isolation system and passive alleviation of possible inner pounding

The existing seismic isolation systems are based on well-known and accepted physical principles, but they are still having some functional drawbacks. As an attempt of improvement, the Roll-N-Cage (RNC) isolator has been recently proposed. It is designed to achieve a balance in controlling isolator displacement demands and structural accelerations. It provides in a single unit all the necessary functions of vertical rigid support, horizontal flexibility with enhanced stability, resistance to low service loads and minor vibration, and hysteretic energy dissipation characteristics. It is characterized by two unique features that are a self-braking (buffer) and a self-recentering mechanism. This paper presents an advanced representation of the main and unique features of the RNC isolator using an available finite element code called SAP2000. The validity of the obtained SAP2000 model is then checked using experimental, numerical and analytical results. Then, the paper investigates the merits and demerits of activating the built-in buffer mechanism on both structural pounding mitigation and isolation efficiency. The paper addresses the problem of passive alleviation of possible inner pounding within the RNC isolator, which may arise due to the activation of its self-braking mechanism under sever excitations such as near-fault earthquakes. The results show that the obtained finite element code-based model can closely match and accurately predict the overall behavior of the RNC isolator with effectively small errors. Moreover, the inherent buffer mechanism of the RNC isolator could mitigate or even eliminate direct structure-tostructure pounding under severe excitation considering limited septation gaps between adjacent structures. In addition, the increase of inherent hysteretic damping of the RNC isolator can efficiently limit its peak displacement together with the severity of the possibly developed inner pounding and, therefore, alleviate or even eliminate the possibly arising negative effects of the buffer mechanism on the overall RNC-isolated structural responses.

Face, content, and construct validity of the EndoViS training system for objective assessment of psychomotor skills of laparoscopic surgeons

Background The aim of this study is to present face, content, and constructs validity of the endoscopic orthogonal video system (EndoViS) training system and determines its efficiency as a training and objective assessment tool of the surgeons’ psychomotor skills. Methods Thirty-five surgeons and medical students participated in this study: 11 medical students, 19 residents, and 5 experts. All participants performed four basic skill tasks using conventional laparoscopic instruments and EndoViS training system. Subsequently, participants filled out a questionnaire regarding the design, realism, overall functionality, and its capabilities to train hand–eye coordination and depth perception, rated on a 5-point Likert scale. Motion data of the instruments were obtained by means of two webcams built into a laparoscopic physical trainer. To identify the surgical instruments in the images, colored markers were placed in each instrument. Thirteen motion-related metrics were used to assess laparoscopic performance of the participants. Statistical analysis of performance was made between novice, intermediate, and expert groups. Internal consistency of all metrics was analyzed with Cronbach’s α test. Results Overall scores about features of the EndoViS system were positives. Participants agreed with the usefulness of tasks and the training capacities of EndoViS system (score >4). Results presented significant differences in the execution of three skill tasks performed by participants. Seven metrics showed construct validity for assessment of performance with high consistency levels. Conclusions EndoViS training system has been successfully validated. Results showed that EndoViS was able to differentiate between participants of varying laparoscopic experience. This simulator is a useful and effective tool to objectively assess laparoscopic psychomotor skills of the surgeons.